תיאור המשרה | Key Qualifications
It takes a strong background in Data Science and Machine Learning to qualify for this job. As an applicant, you will explain not just how to build models to answer problems, but how proved models worked in silica and the real world.
- Minimum of 2 years experience applying machine learning techniques to build models that power products & experiences
- Experienced user of machine learning and statistical-analysis libraries, such as GraphLab Create, scikit-learn, scipy, R, NetworkX, Spacy, and NLTK
- Deep understanding of the algorithms and the ability to tweak algorithms when needed or implement new algorithms
- Strength in one of the following domains: deep learning, NLP, computer vision, recommenders, time series data
- Strong software development skills with proficiency in Python preferred
- Ability to explain and present analyses and machine learning concepts to a broad technical audience
- Creative, collaborative, & product focused
- Experience with Hadoop/Spark ecosystem tools is a plus
- Experience with deep learning frameworks, such as mxnet, Torch, Caffe, and TensorFlow is a plus
- Experience programming in Python,
- Knowledge working with big data tools (Spark/Hadoop, S3/HDFS).
Description
As a member of the machine learning Applications team, you will engage directly relevant product teams such in order to co-develop solutions for a variety of tasks and projects using diverse tools and techniques. You will also be a trusted adviser for methodology practice in machine learning development.
YOUR RESPONSIBILITIES INCLUDE:
- Co-developing machine learning solutions with data scientists and engineers on product teams
- Developing proof-of-concept apps that use machine learning to demonstrate product feature feasibility
- Providing technical guidance to product teams on the choice of machine learning approaches appropriate for a task
- Providing architectural guidance on transitioning prototypes to high-performance production models
- Providing feedback on tools and new features needed back to platform development teams
Education
BSC/ MSC in Computer Science, Electrical Engineering.
PHD IS A PLUS
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